History of Dictionary Searches using Damerau-Levenshtein distance in T-SQL
Fuzzy-string Searches
(up to 100 most recent)
for
"subsample"
| Num | Started At (CA time) | Searched Word | Change Limit | Words Checked | Words Matched | Seconds | Words Per Sec |
| 349 | 2026-01-05 07:19:46 | subsample | 2 | 121436 | 4 | 8.343 | 14555.4 |
| 348 | 2026-01-04 22:43:18 | subsample | 2 | 121436 | 4 | 3.716 | 32679.2 |
| 347 | 2026-01-03 13:49:49 | subsample | 4 | 165329 | 101 | 10.750 | 15379.4 |
| 346 | 2026-01-02 14:57:25 | subsample | 2 | 121436 | 4 | 3.280 | 37023.2 |
| 345 | 2026-01-02 05:53:34 | subsample | 3 | 148641 | 14 | 7.406 | 20070.3 |
| 344 | 2026-01-01 03:56:02 | subsample | 4 | 165329 | 101 | 11.860 | 13940.1 |
| 343 | 2026-01-01 00:01:03 | subsample | 3 | 148641 | 14 | 8.313 | 17880.5 |
| 342 | 2025-12-31 23:58:58 | subsample | 3 | 148641 | 14 | 6.860 | 21667.8 |
| 341 | 2025-12-30 16:59:12 | subsample | 2 | 121436 | 4 | 9.873 | 12299.8 |
| 340 | 2025-12-28 05:48:23 | subsample | 3 | 148641 | 14 | 12.733 | 11673.7 |
| 339 | 2025-12-26 21:48:29 | subsample | 3 | 148641 | 14 | 10.436 | 14243.1 |
| 338 | 2025-12-25 15:37:41 | subsample | 3 | 148641 | 14 | 7.763 | 19147.4 |
| 337 | 2025-12-24 21:29:14 | subsample | 1 | 81242 | 3 | 1.500 | 54161.3 |
| 336 | 2025-12-24 17:39:21 | subsample | 3 | 148641 | 14 | 6.643 | 22375.6 |
| 335 | 2025-12-24 12:42:00 | subsample | 1 | 81242 | 3 | 2.876 | 28248.3 |
| 334 | 2025-12-24 09:23:18 | subsample | 1 | 81242 | 3 | 3.890 | 20884.8 |
| 333 | 2025-12-23 18:45:54 | subsample | 2 | 121436 | 4 | 3.906 | 31089.6 |
| 332 | 2025-12-21 18:04:01 | subsample | 2 | 121436 | 4 | 5.156 | 23552.4 |
| 331 | 2025-12-21 17:06:17 | subsample | 2 | 121436 | 4 | 3.623 | 33518.1 |
| 330 | 2025-12-21 17:03:58 | subsample | 2 | 121436 | 4 | 3.283 | 36989.3 |
| 329 | 2025-12-18 19:46:10 | subsample | 3 | 148641 | 14 | 7.470 | 19898.4 |
| 328 | 2025-12-18 15:34:19 | subsample | 2 | 121436 | 4 | 3.703 | 32794.0 |
| 327 | 2025-12-17 16:34:02 | subsample | 2 | 121436 | 4 | 3.610 | 33638.8 |
| 326 | 2025-12-16 09:01:55 | subsample | 1 | 81242 | 3 | 1.440 | 56418.1 |
| 325 | 2025-12-12 23:05:44 | subsample | 1 | 81242 | 3 | 1.483 | 54782.2 |
| 324 | 2025-12-04 20:56:53 | subsample | 1 | 81242 | 3 | 1.530 | 53099.3 |
| 323 | 2025-12-02 03:05:18 | subsample | 2 | 121436 | 4 | 3.716 | 32679.2 |
| 322 | 2025-12-01 06:46:55 | subsample | 4 | 165329 | 101 | 24.940 | 6629.1 |
| 321 | 2025-11-24 22:57:36 | subsample | 1 | 81242 | 3 | 1.436 | 56575.2 |
| 320 | 2025-11-21 17:39:13 | subsample | 1 | 81242 | 3 | 1.500 | 54161.3 |
| 319 | 2025-11-19 23:35:05 | subsample | 3 | 148641 | 14 | 15.486 | 9598.4 |
| 318 | 2025-11-18 12:22:40 | subsample | 1 | 81242 | 3 | 1.530 | 53099.3 |
| 317 | 2025-11-17 20:38:00 | subsample | 1 | 81242 | 3 | 1.406 | 57782.4 |
| 316 | 2025-11-17 08:25:10 | subsample | 1 | 81242 | 3 | 1.656 | 49059.2 |
| 315 | 2025-11-16 01:35:11 | subsample | 1 | 81242 | 3 | 1.530 | 53099.3 |
| 314 | 2025-11-14 00:47:04 | subsample | 4 | 165329 | 101 | 12.703 | 13015.0 |
| 313 | 2025-11-13 02:27:41 | subsample | 3 | 148641 | 14 | 7.343 | 20242.5 |
| 312 | 2025-11-08 01:15:03 | subsample | 2 | 121436 | 4 | 3.296 | 36843.4 |
| 311 | 2025-11-03 13:19:45 | subsample | 1 | 81242 | 3 | 1.796 | 45235.0 |
| 310 | 2025-10-24 23:53:13 | subsample | 1 | 81242 | 3 | 1.453 | 55913.3 |
| 309 | 2025-10-20 02:06:02 | subsample | 1 | 81242 | 3 | 4.560 | 17816.2 |
| 308 | 2025-10-17 21:37:52 | subsample | 1 | 81242 | 3 | 1.423 | 57092.1 |
| 307 | 2025-10-17 14:00:58 | subsample | 1 | 81242 | 3 | 1.530 | 53099.3 |
| 306 | 2025-10-16 01:44:48 | subsample | 1 | 81242 | 3 | 1.280 | 63470.3 |
| 305 | 2025-10-13 09:57:47 | subsample | 1 | 81242 | 3 | 1.733 | 46879.4 |
| 304 | 2025-10-11 05:39:01 | subsample | 3 | 148641 | 14 | 7.390 | 20113.8 |
| 303 | 2025-09-24 00:15:34 | subsample | 1 | 81242 | 3 | 1.550 | 52414.2 |
| 302 | 2025-09-18 18:14:13 | subsample | 1 | 81242 | 3 | 1.953 | 41598.6 |
| 301 | 2025-09-17 18:09:40 | subsample | 1 | 81242 | 3 | 1.470 | 55266.7 |
| 300 | 2025-09-16 21:27:40 | subsample | 1 | 81242 | 3 | 1.513 | 53696.0 |
| 299 | 2025-09-16 17:40:08 | subsample | 1 | 81242 | 3 | 1.406 | 57782.4 |
| 298 | 2025-09-16 09:45:18 | subsample | 3 | 148641 | 14 | 6.063 | 24516.1 |
| 297 | 2025-09-15 16:10:53 | subsample | 1 | 81242 | 3 | 1.343 | 60492.9 |
| 296 | 2025-09-15 15:47:40 | subsample | 1 | 81242 | 3 | 5.280 | 15386.7 |
| 295 | 2025-09-15 01:02:59 | subsample | 1 | 81242 | 3 | 1.500 | 54161.3 |
| 294 | 2025-09-13 05:24:54 | subsample | 1 | 81242 | 3 | 1.453 | 55913.3 |
| 293 | 2025-09-03 05:52:37 | subsample | 3 | 148641 | 14 | 6.936 | 21430.4 |
| 292 | 2025-09-02 05:54:37 | subsample | 3 | 148641 | 14 | 6.483 | 22927.8 |
| 291 | 2025-08-31 02:59:30 | subsample | 1 | 81242 | 3 | 1.500 | 54161.3 |
| 290 | 2025-08-29 19:02:11 | subsample | 1 | 81242 | 3 | 1.500 | 54161.3 |
| 289 | 2025-08-26 19:24:26 | subsample | 1 | 81242 | 3 | 1.296 | 62686.7 |
| 288 | 2025-08-18 17:48:52 | subsample | 1 | 81242 | 3 | 1.516 | 53589.7 |
| 287 | 2025-08-05 21:00:20 | subsample | 3 | 148641 | 14 | 17.003 | 8742.0 |
| 286 | 2025-08-04 13:46:04 | subsample | 3 | 148641 | 14 | 6.796 | 21871.8 |
| 285 | 2025-08-03 13:26:53 | subsample | 3 | 148641 | 14 | 5.966 | 24914.7 |
| 284 | 2025-07-25 08:09:44 | subsample | 1 | 81242 | 3 | 2.843 | 28576.2 |
| 283 | 2025-07-24 03:13:20 | subsample | 1 | 81242 | 3 | 3.360 | 24179.2 |
| 282 | 2025-06-22 05:31:21 | subsample | 3 | 148641 | 14 | 36.936 | 4024.3 |
| 281 | 2025-06-22 01:06:11 | subsample | 2 | 121436 | 4 | 18.813 | 6454.9 |
| 280 | 2025-06-21 10:34:27 | subsample | 1 | 81242 | 3 | 3.203 | 25364.3 |
| 279 | 2025-06-14 10:30:51 | subsample | 1 | 81242 | 3 | 6.970 | 11656.0 |
| 278 | 2025-06-14 01:01:54 | subsample | 1 | 81242 | 3 | 9.220 | 8811.5 |
| 277 | 2025-05-30 11:53:45 | subsample | 1 | 81242 | 3 | 6.546 | 12410.9 |
| 276 | 2025-04-20 01:46:50 | subsample | 1 | 81242 | 3 | 7.030 | 11556.5 |
| 275 | 2025-03-29 17:26:19 | subsample | 2 | 121436 | 4 | 23.393 | 5191.1 |
| 274 | 2025-03-27 22:49:18 | subsample | 1 | 81242 | 3 | 3.623 | 22424.0 |
| 273 | 2025-03-07 01:20:47 | subsample | 4 | 165329 | 101 | 122.006 | 1355.1 |
| 272 | 2025-03-07 01:20:44 | subsample | 3 | 148641 | 14 | 80.973 | 1835.7 |
| 271 | 2025-03-07 01:20:43 | subsample | 2 | 121436 | 4 | 36.500 | 3327.0 |
| 270 | 2025-03-07 00:46:47 | subsample | 1 | 81242 | 3 | 6.436 | 12623.1 |
| 269 | 2025-02-25 03:57:31 | subsample | 3 | 148641 | 14 | 28.016 | 5305.6 |
| 268 | 2025-02-25 03:57:32 | subsample | 2 | 121436 | 4 | 27.156 | 4471.8 |
| 267 | 2025-02-24 12:23:19 | subsample | 3 | 148641 | 14 | 35.610 | 4174.1 |
| 266 | 2025-02-20 03:28:23 | subsample | 3 | 148641 | 14 | 49.080 | 3028.5 |
| 265 | 2025-02-20 03:28:32 | subsample | 3 | 148641 | 14 | 36.096 | 4117.9 |
| 264 | 2025-02-20 03:28:20 | subsample | 2 | 121436 | 4 | 17.280 | 7027.5 |
| 263 | 2025-02-20 03:26:20 | subsample | 1 | 81242 | 3 | 7.986 | 10173.1 |
| 262 | 2025-02-19 23:28:49 | subsample | 3 | 148641 | 14 | 48.050 | 3093.5 |
| 261 | 2025-02-19 22:25:13 | subsample | 4 | 165329 | 101 | 45.236 | 3654.8 |
| 260 | 2025-02-19 22:25:12 | subsample | 3 | 148641 | 14 | 44.550 | 3336.5 |
| 259 | 2025-02-19 22:23:41 | subsample | 1 | 81242 | 3 | 6.393 | 12708.0 |
| 258 | 2025-02-12 22:42:17 | subsample | 1 | 81242 | 3 | 6.706 | 12114.8 |
| 257 | 2025-01-29 06:10:22 | subsample | 2 | 121436 | 4 | 18.330 | 6625.0 |
| 256 | 2025-01-26 20:39:18 | subsample | 3 | 148641 | 14 | 28.053 | 5298.6 |
| 255 | 2025-01-26 20:39:19 | subsample | 2 | 121436 | 4 | 17.770 | 6833.8 |
| 254 | 2025-01-26 20:32:40 | subsample | 1 | 81242 | 3 | 1.423 | 57092.1 |
| 253 | 2025-01-11 17:41:17 | subsample | 1 | 81242 | 3 | 4.296 | 18911.1 |
| 252 | 2025-01-05 06:36:50 | subsample | 3 | 148641 | 14 | 37.173 | 3998.6 |
| 251 | 2025-01-03 06:37:54 | subsample | 4 | 165329 | 101 | 79.990 | 2066.9 |
| 250 | 2025-01-02 14:14:46 | subsample | 3 | 148641 | 14 | 24.423 | 6086.1 |